Results 21 to 30 of about 283,485 (287)

Improving Autoregressive NMT with Non-Autoregressive Model [PDF]

Proceedings of the First Workshop on Automatic Simultaneous Translation, 2020
Autoregressive neural machine translation (NMT) models are often used to teach non-autoregressive models via knowledge distillation. However, there are few studies on improving the quality of autoregressive translation (AT) using non-autoregressive translation (NAT).
Long Zhou, Jiajun Zhang, Chengqing Zong
openaire   +1 more source

Forecasting the development of electricity from renewable energy sources in Poland against the background of the European Union countries

Economics and Environment, 2023
One of the key elements in the development of countries is energy stability particularly related to ensuring, among other things, continuity of power supply.
Marcin Stanuch, Krzysztof Adam Firlej
doaj   +1 more source

Bayesian Model Selection for Beta Autoregressive Processes [PDF]

, 2010
We deal with Bayesian inference for Beta autoregressive processes. We restrict our attention to the class of conditionally linear processes. These processes are particularly suitable for forecasting purposes, but are difficult to estimate due to the ...
Casarin, R., Leisen, F., Valle, L. Dalla
core   +2 more sources

Autoregressive functions estimation in nonlinear bifurcating autoregressive models [PDF]

Statistical Inference for Stochastic Processes, 2016
Bifurcating autoregressive processes, which can be seen as an adaptation of au-toregressive processes for a binary tree structure, have been extensively studied during the last decade in a parametric context. In this work we do not specify any a priori form for the two autoregressive functions and we use nonparametric techniques.
Bitseki Penda, Siméon Valère, Olivier, Adélaïde   +1 more
openaire   +2 more sources

Model Selection in Threshold Models [PDF]

, 2004
This paper considers information criteria as model evaluation tools for nonlinear threshold models. Results concerning the consistency of information criteria in selecting the lag order of linear autoregressive models are extended to nonlinear ...
Kapetanios, George
core   +1 more source

Learned Lossless Image Compression With Combined Channel-Conditioning Models and Autoregressive Modules

IEEE Access, 2023
Lossless image compression is an important research field in image compression. Recently, learning-based lossless image compression methods achieved impressive performance compared with traditional lossless methods, such as WebP, JPEG2000, and FLIF.
Ran Wang, Jinming Liu, Heming Sun, Jiro Katto   +3 more
doaj   +1 more source

Auxiliary Guided Autoregressive Variational Autoencoders [PDF]

, 2018
Generative modeling of high-dimensional data is a key problem in machine learning. Successful approaches include latent variable models and autoregressive models. The complementary strengths of these approaches, to model global and local image statistics
Lucas, Thomas, Verbeek, Jakob
core   +4 more sources

Track Prediction for HF Radar Vessels Submerged in Strong Clutter Based on MSCNN Fusion with GRU-AM and AR Model

Remote Sensing, 2021
High-frequency (HF) surface-wave radar has a wide range of applications in marine monitoring due to its long-distance, wide-area, and all-weather detection ability.
Ling Zhang, Jingzhi Zhang, Jiong Niu, Q. M. Jonathan Wu, Gangsheng Li   +4 more
doaj   +1 more source

A Novel Method of Adaptive Kalman Filter for Heading Estimation Based on an Autoregressive Model

Applied Sciences, 2019
With the popularity of smartphones and the development of microelectromechanical system (MEMS), the pedestrian dead reckoning (PDR) algorithm based on the built-in sensors of a smartphone has attracted much research.
Dashuai Chai, Guoliang Chen, Shengli Wang   +2 more
doaj   +1 more source

A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue

Sensors, 2022
Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and ...
Giovanni Corvini, Silvia Conforto
doaj   +1 more source